5.1.2. Baseline

To demonstrate the effectiveness of our approach, we define several baseline methods for comparison. In the experiments, these methods are configured as:


The SVM, KNN and XGBoost are based on scikit-learn [34]. The features feed to SVM, KNN and XGBoost are produced by Truncated Singular Value Decomposition(TruncatedSVD) from samples. The dimension of features configured as 50. MLP-3 and ResNet-20 are launched upon tensorflow. Further, they are trained on origin samples.
